Erythropoiesis is a dynamic process governed by quantitative changes in the relative levels of transcription fac- tors (TFs). Due to the current paucity of quantitative data on the proteins that constitute the transcriptional regu- latory network (TRN), most models of erythropoiesis are based primarily on mRNA measurements and do not typically consider changes in the protein levels of specific TFs. This significantly limits the understanding of erythropoiesis and other transcriptionally regulated processes such as -globin expression, ultimately impinging on the capacity to correct hemoglobin disorders. The long-term goal is to decipher the TRN that controls eryth- ropoiesis in health and disease. The objective of this proposal is to significantly expand our TRN model for cell fate decision during erythropoiesis by integrating dynamic bulk and single cell TF protein abundance measure- ments with other transcription-relevant -omics data. The central hypothesis is that the relative protein levels of TFs are critical parameters in the establishment of proper gene expression programs during the continuum of differentiation, and that erythropoiesis is driven by graded changes in the relative amounts of specific combina- tions of TFs. The rationale is that integration of the dynamic and quantitative nature of the TF proteome into an expanded TRN of erythropoiesis will result in a model with improved predictive power which will serve as a benchmark for healthy erythropoiesis against which to compare erythroid-related disease states, and will facili- tate the identification of pharmacological agents to restore normal erythropoiesis. Three specific aims have been designed: 1) Absolute quantification of the TF proteome during erythropoiesis; 2) Determine how gradual changes in the abundance of multiple TFs in single cells initiate and progressively reinforce cell fate decisions along the erythroid trajectory; and 3) Computational analysis, modeling and validation of the erythropoiesis TRN. For the first aim, a high throughput quantitative mass spectrometry (MS) approach will be used to measure absolute levels of the TF proteome during ex vivo erythropoiesis of HSPCs derived from healthy donors. For the second aim, complementary CyTOF and targeted-MS proteomic approaches will be combined to estimate TF protein abundances in single cells, with other single cell ?omics technologies to measure changes in gene ex- pression and TF genomic binding during ex vivo erythropoiesis. Under the third aim, TRN models of erythropoi- esis will be built utilizing measurements of TF protein abundances, and other transcription-relevant ?omics data. Functional validation will be performed for TFs that have been implicated in transcriptional control during eryth- ropoiesis based on our recent results. The approach is innovative because it uses a novel combination of single cell and bulk proteomics methodologies to quantify large numbers of TFs during erythropoiesis in primary human cells and uses the data for integrative TRN modeling. The proposed research is significant because it will illumi- nate complex regulatory processes that control erythropoiesis. Ultimately, such knowledge has the potential to guide the design of new therapeutics to re-establish proper -globin expression in -thalassemic patients.